Snow Losses for Different PV Module Designs: Modelling and Validation in Southern Finland

As PV systems are becoming more common in regions with significant snow cover during winter, improving the accuracy of the snow loss prediction and monitoring is crucial. In this work, we propose a novel hybrid snow loss model that differentiates between snow loss discrepancies in full-cell and half-cell modules. Snow coverage on PV modules is evaluated using an image processing algorithm, and the interconnection between PV cells and modules is incorporated through a cell-level electrical model. Using these methods, we performed an analysis of PV snow losses for both module types in a testing system situated in southern Finland during the winter of 2023-2024. The results show that half-cell modules reduce annual snow losses by approximately 26% compared to full-cell modules. In contrast to the Marion model, this mitigating effect of half-cell modules is well reflected in our modeling results. Furthermore, our model outperforms the Marion model in predicting time-dependent snow losses, reducing the RMSE by a factor of around 3. This improvement is essential for accurate performance monitoring and forecasting in snow-affected PV systems.